Datasets:
row_id string | series_id string | ph_rank int64 | organism string | strain_id string | antibiotic_name string | antibiotic_class string | ph_value float64 | exposure_index float64 | mic_mg_L float64 | cfu0_log10 float64 | cfu24_log10 float64 | kill_24_log10 float64 | media string | assay_method string | source_type string | ph_decay_signal int64 | earliest_ph_decay int64 | notes string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ABXPD010-TR-0001 | S1 | 1 | Escherichia coli | EC-ATCC25922 | azithromycin | macrolide | 7 | 1 | 2 | 7.2 | 5.2 | 2 | CAMHB | ph_time_kill | simulated | 0 | 0 | reference pH |
ABXPD010-TR-0002 | S1 | 2 | Escherichia coli | EC-ATCC25922 | azithromycin | macrolide | 7.4 | 1 | 2 | 7.2 | 5.1 | 2.1 | CAMHB | ph_time_kill | simulated | 0 | 0 | stable |
ABXPD010-TR-0003 | S1 | 3 | Escherichia coli | EC-ATCC25922 | azithromycin | macrolide | 6.8 | 1 | 2 | 7.2 | 5.3 | 1.9 | CAMHB | ph_time_kill | simulated | 0 | 0 | small drift |
ABXPD010-TR-0004 | S1 | 4 | Escherichia coli | EC-ATCC25922 | azithromycin | macrolide | 6.5 | 1 | 2 | 7.2 | 5.35 | 1.85 | CAMHB | ph_time_kill | simulated | 0 | 0 | still acceptable |
ABXPD010-TR-0005 | S1 | 5 | Escherichia coli | EC-ATCC25922 | azithromycin | macrolide | 6 | 1 | 2 | 7.2 | 5.6 | 1.6 | CAMHB | ph_time_kill | simulated | 0 | 0 | low pH weaker but not collapse |
ABXPD010-TR-0006 | S2 | 1 | Pseudomonas aeruginosa | PA-CLIN120 | tobramycin | aminoglycoside | 7 | 1 | 1 | 7.3 | 5.2 | 2.1 | CAMHB | ph_time_kill | simulated | 0 | 0 | reference pH |
ABXPD010-TR-0007 | S2 | 2 | Pseudomonas aeruginosa | PA-CLIN120 | tobramycin | aminoglycoside | 7.4 | 1 | 1 | 7.3 | 5.25 | 2.05 | CAMHB | ph_time_kill | simulated | 0 | 0 | stable |
ABXPD010-TR-0008 | S2 | 3 | Pseudomonas aeruginosa | PA-CLIN120 | tobramycin | aminoglycoside | 6.8 | 1 | 1 | 7.3 | 6.1 | 1.2 | CAMHB | ph_time_kill | simulated | 1 | 1 | collapse in physiologic low edge |
ABXPD010-TR-0009 | S2 | 4 | Pseudomonas aeruginosa | PA-CLIN120 | tobramycin | aminoglycoside | 6.5 | 1 | 1 | 7.3 | 6.4 | 0.9 | CAMHB | ph_time_kill | simulated | 1 | 0 | collapse persists |
ABXPD010-TR-0010 | S2 | 5 | Pseudomonas aeruginosa | PA-CLIN120 | tobramycin | aminoglycoside | 6 | 1 | 1 | 7.3 | 6.6 | 0.7 | CAMHB | ph_time_kill | simulated | 1 | 0 | worse at low pH |
ABX-PD-010 pH-Dependent Activity Decay
Purpose
Detect collapse of antibiotic killing across physiologic pH.
Core idea
Use pH 7.0 as a reference inside each series.
Flag decay when killing drops sharply at pH values that still occur in vivo.
Physiologic window used in v1
- 6.8 to 7.6
Files
- data/train.csv
- data/test.csv
- scorer.py
Schema
Each row is one pH condition.
Required columns
- row_id
- series_id
- ph_rank
- organism
- strain_id
- antibiotic_name
- antibiotic_class
- ph_value
- exposure_index
- mic_mg_L
- cfu0_log10
- cfu24_log10
- kill_24_log10
- media
- assay_method
- source_type
- ph_decay_signal
- earliest_ph_decay
Labels
ph_decay_signal
- 1 for rows at or after the first detected collapse
earliest_ph_decay
- 1 only for the first detected row in that series
Scorer logic in v1
- require a single reference row at pH 7.0
- call decay when
- pH is inside 6.8 to 7.6
- kill drops by 0.8 log10 or more vs reference
- exposure_index stays within 10 percent of reference
- MIC stays within 2 fold of reference
Evaluation
Run
- python scorer.py --path data/test.csv
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